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Title: Hyperspectral imaging for head and neck cancer detection: specular glare and variance of the tumor margin in surgical specimens
Authors: Halicek, Martin
Fabelo Gómez, Himar Antonio 
Ortega Sarmiento, Samuel 
Little, James V.
Wang, Xu
Chen, Amy Y.
Marrero Callicó, Gustavo Iván 
Myers, Larry
Sumer, Baran D.
Fei, Baowei
UNESCO Clasification: 3314 Tecnología médica
Keywords: Squamous-Cell Carcinoma
Issue Date: 2019
Project: Identificación Hiperespectral de Tumores Cerebrales (Ithaca)
Journal: Journal of Medical Imaging 
Abstract: Head and neck squamous cell carcinoma (SCC) is primarily managed by surgical cancer resection. Recurrence rates after surgery can be as high as 55%, if residual cancer is present. Hyperspectral imaging (HSI) is evaluated for detection of SCC in ex-vivo surgical specimens. Several machine learning methods are investigated, including convolutional neural networks (CNNs) and a spectral-spatial classification framework based on support vector machines. Quantitative results demonstrate that additional data preprocessing and unsupervised segmentation can improve CNN results to achieve optimal performance. The methods are trained in two paradigms, with and without specular glare. Classifying regions that include specular glare degrade the overall results, but the combination of the CNN probability maps and unsupervised segmentation using a majority voting method produces an area under the curve value of 0.81 [0.80, 0.83]. As the wavelengths of light used in HSI can penetrate different depths into biological tissue, cancer margins may change with depth and create uncertainty in the ground truth. Through serial histological sectioning, the variance in the cancer margin with depth is investigated and paired with qualitative classification heat maps using the methods proposed for the testing group of SCC patients. The results determined that the validity of the top section alone as the ground truth may be limited to 1 to 2 mm. The study of specular glare and margin variation provided better understanding of the potential of HSI for the use in the operating room.
ISSN: 2329-4302
DOI: 10.1117/1.JMI.6.3.035004
Source: Journal of Medical Imaging [ISSN 2329-4302], v. 6 (3), 035004
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